Purpose – Although the topic of knowledge management (KM) failure has emerged over the past several years, no specific theory has been proposed about the ability of an organization to discover and manage unexpected failures in the organizational capabilities of KM. Thus, the main aim of this paper is to develop a theory of KM reliability by taking into account the availability of existing theory of high reliability for organizations. Furthermore, this study aims to empirically evaluate the impact of a reliable KM on organizational performance by developing a reliability measurement instrument. Design/methodology/approach – The study develops and tests a theoretical framework whereby the reliable KM is supported on its reliability aspects and organizational performance on its financial, process, and internal aspects. Based on a questionnaire, data were obtained from a sample of 254 companies in North America. The measurement model was tested and confirmed by using structural equation modeling (SEM). Findings – The results show that the reliable KM has a multi-dimensional structure as described by the proposed theoretical framework. Additionally, the results underscore the importance of KM reliability in creating conditions favorable for a firm's success. Practical implications – It was verified that the reliable KM affects the measures of organizational performance, including financial, process, and internal performance. This is useful for researchers and executives looking for appropriate outcomes through the implementation of KM initiatives. Furthermore, this study provides a starting point for further research on KM reliability. Originality/value – This study claims that a key to successful KM is to create a cognitive infrastructure that enables simultaneous adaptive learning and provides an organizational reliability infrastructure through the management of unwanted, unanticipated, and unexplainable failures in the KM's required capabilities.

Purpose – A perfect knowledge management (KM) initiative is one that achieves its objectives without any failure during a pre-defined period. However, KM implementation is not perfect in every organization as it requires substantial changes in organizational infrastructures, including culture, structure, and technology. Therefore, the purpose of this paper is to propose a model for assessing the reliability of KM to help organizations evaluate their ability to implement KM successfully by identifying key reliability variables, modeling the complex interaction structure among variables, and determining the probability of failure for each KM capability. Design/methodology/approach – In this study, relevant variables are identified by a thorough analysis of related references in literature. In order to determine the compound structure of complicated interactions among variables, a group-based approach is utilized. Based on the combined cognitive maps, a cognitive network is constructed as a framework for graphically representing the logical relationships between variables and capturing the uncertainty in the dependency among these variables using conditional probabilities. The applicability of the proposed approach and the efficacy of the model was verified and validated with data from a banking institution. Findings – Results show that KM reliability can be defined by the degree to which required KM capabilities, including infrastructure and process capabilities, have the ability to perform as intended in a certain organizational environment. Furthermore, it is demonstrated that reliability assessment of KM through a hybrid approach of fuzzy cognitive map and Bayesian network is possible and useful. Practical implications – The proposed reliability assessment model facilitates the process of understanding why and how failures occur in KM. Moreover, the proposed approach evaluates the probability of success for each variable as well as for the entire KM initiative. Therefore, it can provide insight for managers and executives into the degree of reliability for their existing KM and prevention of failures in vital factors through necessary actions. Originality/value – The suggested approach to KM reliability assessment is a novel method that provides powerful arguments for a more holistic view of KM reliability factors, which is crucial for the successful implementation of KM.

Purpose -As a way of assessing the ability of organizations to discover and manage unexpected failures in organizational capabilities of knowledge management (KM), this study aims to develop a measurement instrument that involves the five reliability dimensions of preoccupation with failure, reluctance to simplify interpretations, sensitivity to operations, commitment to resilience, and deference to expertise. Design/methodology/approach -To generate measurement items, previous research related to organizational reliability, high reliability theory, mindfulness, and required organizational capabilities of KM was reviewed. The measurement instrument was then verified in terms of reliability and validity, empirically using data from 240 companies in North America. Internal consistency of measurements, measurement item reliability, and construct reliability were examined to ensure the reliability of the instrument. Based on confirmatory factor analysis using structural equation modelling, construct validity was also tested. Findings -The reliability evaluation instrument for KM suggested in this study was constructed with four dimensions, preoccupation with failure in KM, sensitivity to KM operations, commitment to resilience in KM, and deference to expertise. The related measurement items were also identified. Practical implications -This instrument is useful for researchers and executives looking for appropriate outcomes through the implementation of KM initiatives. Furthermore, the study provides a starting point for further research on KM reliability. Originality/value -To date, while many of the KM success or failure studies have relied on developing success factors or organizational capability requirements, few studies have been conducted to identify evaluation measures that can assess the cognitive infrastructure that enables simultaneous adaptive learning and provides organizational reliability infrastructure through the management of unwanted, unanticipated, and unexplainable failures in KM-required capabilities.

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Purpose – The purpose of this paper is to develop a novel hybrid multi-criteria decision-making (MCDM) model to help organizations select their knowledge-based strategy effectively. Knowledge management (KM) initiatives are often started with the selection of a strategy, which is a critical decision for a successful KM implementation. Design/methodology/approach – KM initiatives are often started with the selection of a strategy, which is a critical decision for a successful KM implementation. Thus, the aim of this paper is to develop a novel hybrid MCDM model to help organizations select their knowledge-based strategy effectively. Findings – Results illustrate that the proposed model is efficient to consider the complex interactions among criteria and provides a consistent decision with less pair-wise comparisons. Furthermore, a case study indicates that a “codification versus tacitness” strategy is preferred over other strategies considering nine main domain criteria. Originality/value – The contribution of this paper is threefold: it addresses the gaps in KM literature on the effective and efficient assessment of KM strategy selection; it provides a comprehensive and systematic framework that combines analytic network process (ANP) and consistent fuzzy preference relations (CFPR) to assess KM implementation strategy; and it illustrates a real-world study to exhibit the applicability of the proposed approach and the efficacy of the framework.